KUALA LUMPUR, Oct 24 (Bernama) -- Jumio, an automated, end-to-end identity verification, risk assessment and compliance solutions provider, has launched Jumio 360° Fraud Analytics, at Money20/20 the United States of America (USA).
According to Jumio in a statement, its new fraud-fighting technology uses artificial intelligence (AI)-driven predictive analytics to identify fraud patterns with more sophistication and accuracy than ever before.
“Today we are pushing the industry to evolve once again by harnessing the power of predictive analytics to identify fraud patterns across our vast network.
“This will allow us to identify and stop fraud rings and other coordinated attacks with more accuracy than ever before,” said Jumio Chief Executive Officer, Robert Prigge.
Jumio’s analysis found that 25 per cent of fraud is interconnected, either perpetrated by fraud rings or by individuals using the same information or credentials to open new accounts on banking sites, ecommerce platforms, sharing economy sites and more.
Its new technology tackles this problem using graph database technology with a layer of machine learning, as it groups identity transactions into clusters across the network and determines the fraud risk of each cluster which provides a multi-dimensional view of each transaction and the cross-customer ecosystem as a whole.
With the addition of Jumio 360° Fraud Analytics, the identity transaction will also be compared to the clusters and generate a predictive fraud score that can be used to automatically reject the transaction if it exceeds a certain threshold.
The company’s initial studies show that this approach improves its existing, highly accurate fraud detection rate by at least 30 per cent, without increasing the false rejection rate. Business users can audit the reasons behind the decision in its Portal or via Application Programming Interfaces (APIs).
Jumio 360° Fraud Analytics is currently available in early release to select customers and will be generally available in early 2024.
-- BERNAMA
No comments:
Post a Comment